SINAPSE neutron-gamma discrimination
Context This dataset contains signals collected with the VENDETA detection array at theLos Alamos National Laboratory (LANL) facility, from the spontaneous fission of $^240Pu$. It is intended to support the development and benchmarking ofneutron-gamma discrimination tech
Context
This dataset contains signals collected with the VENDETA detection array at the
Los Alamos National Laboratory (LANL) facility, from the spontaneous fission of
$^240Pu$. It is intended to support the development and benchmarking of
neutron-gamma discrimination techniques, with a particular focus on the
low charge (low light output) regime. Experimental details are described
in Syrett et al. (2025).
Dataset description
The dataset is provided as a single HDF5 file: SINAPSE-neutron_gamma.hdf5.
The file contains 4 subsets, spanning different light output and $$ ranges:
| Subset | Light Ouput Range [keVee] | beta range | description |
| train | 200 – 510 | 0.0 – 0.6 | training set |
| val | 100 – 200 | 0.0 – 0.6 | validation set |
| test | 0 – 200 | 0.0 – 0.6 | test set |
| prompt_gamma | 0 – 100 | 0.8 – 1.2 | pure gamma ray set |
Each subset exposes 3 fields:
| Field | Type | Description |
| waveform | array of float32 | Digitized pulse waveforms, z-score normalized |
| light_output_MeVee | float32 | Light output in MeVee |
| label | int16 | Label: 0: $$, 1: neutron, -1: unidentified |
Example usage
import h5py
with h5py.File("SINAPSE-neutron_gamma.hdf5", "r") as file:
train_samples = file["dataset/train/samples"][:]
train_dataset =
"waveform": train_samples["waveform"],
"light_output_MeVee": train_samples["light_output_MeVee"],
"label": train_samples["label"],
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Files are hosted on the source repository. Click download to access the full dataset.